TYC Soiree: Bilge Yildiz (MIT) & Kenneth Harris (UCL)

Venue: XLG1 LT, Christopher Ingold Building, Gordon Street, UCL In this soiree Prof Bilge Yildiz from MIT will explain how protonic electrochemical synapses can be used for energy-efficient brain-inspired computing and Prof Kenneth Harris will explain how he is using neuropixel probes to study how brain operates and challenges for neuromorphic electronics.
Loading Events

TYC Soiree: Bilge Yildiz (MIT) & Kenneth Harris (UCL)

7 March 2024 @ 2:00 pm 4:00 pm

Venue: XLG1 Christopher Ingold Building, Gordon Street

In this soiree Prof Bilge Yildiz from MIT will explain how protonic electrochemical synapses can be used for energy-efficient brain-inspired computing and Prof Kenneth Harris will explain how he is using neuropixel probes to study how brain operates and challenges for neuromorphic electronics.

Protonic Electrochemical Synapses for Energy-Efficient Brain-Inspired Computing – Bilge Yildiz, Massachusetts Institute of Technology

In this talk, I will share our work on the ionic electrochemical synapses, whose electronic conductivity we control deterministically by electrochemical insertion/extraction of dopant ions into/out of the channel layer. This work is motivated by the need to enable significant reductions in the energy consumption of computing, and is inspired by the ionic processes in the brain. Proton as the working ion in our research presents with very low energy consumption, on par with biological synapses in the brain. Our modeling results indicate the desirable material properties, such as ion conductivity and interface charge transfer kinetics, that we must achieve for fast (ns), low energy (< fJ) and low voltage (<1V) performance of these devices. Importantly, the conductance change in these electrochemical devices depends non-linearly on the gate voltage, due to field-enhanced ion migration in the electrolyte, and charge transfer kinetics at the electrolyte-channel interface. We are leveraging these intrinsic nonlinearities to emulate bio-realistic learning rules deduced from neuroscience studies, such as spike timing dependence of plasticity and Hebbian learning rules. Our findings indicate that protonic electrochemical synapses can serve as energy-efficient and reliable building blocks for brain-inspired computing hardware.

Probing and emulating neuron activity with electronic devices – Kenneth Harris, UCL